nlp engineer

Xantura Limited

<div>
 
 
 Department:
 
 Platform Delivery
 
 
 
 Location:
 
 London
 
 
 
 
 Description
 
 
 
 In this role you will work in the Platform team &ndash; a function for the deployment and evolution of the backend platform that underpins the core of the Xantura business.
 
 
 
 The Role
 
 
 
 You'll own and evolve Xantura's text analytics platform (XTA), the NLP system that extracts structured intelligence from unstructured case notes across health, housing, and social care. You'll work across the full spectrum of NLP: from classical text classification and entity extraction through to LLM-based information extraction, embedding models, and retrieval systems. As the platform matures, you'll help shape our agentic AI capabilities.
 
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Own and evolve the core text analytics pipeline; advancing large-scale concept extraction, classification, and information retrieval across complex social and clinical text corpora.
 </li>
 <li>
 Design and implement LLM-based processing chains for structured information extraction, leveraging prompt engineering, output parsing, and model orchestration to produce high-quality, auditable outputs at scale.
 </li>
 <li>
 Build and manage embedding infrastructure; training, fine-tuning, and serving embedding models, and setting up and operating vector databases to enable semantic search and retrieval across client data.
 </li>
 <li>
 Develop and maintain classical NLP components where appropriate; training smaller classifiers, entity recognisers, and domain-specific models for tasks where efficiency and interpretability outweigh generative approaches.
 </li>
 <li>
 Lay the groundwork for agentic AI capabilities as the platform evolves; contributing to the design of multi-agent orchestration, tool integration, and conversational interfaces over Xantura's services.
 </li>
 <li>
 Ensure all NLP systems are robust, explainable, and aligned with Responsible AI principles; essential where outputs inform decisions about vulnerable people in health and social care.
 
 
 
 
 </li>
 </ul>
 
 Skills, Knowledge &amp; Expertise
 
 
 
 <ul>
 <li>
 Bachelor's or Master's degree in Computer Science, Computational Linguistics, Machine Learning, or a related technical field, or equivalent practical experience.
 </li>
 <li>
 3+ years of professional experience in an NLP, ML, or AI engineering role
 </li>
 <li>
 Strong programming skills and production experience in Python.
 </li>
 </ul>
 
 Clear evidence of practical experience across some or all of the following:
 
 <ul>
 <li>
 LLM utilisation in production; prompt engineering, output structuring, chaining, and integrating LLMs into data processing pipelines (e.g. via LangChain, PydanticAI, or similar);
 </li>
 <li>
 Embedding models; training, fine-tuning, or serving embedding models (e.g. sentence-transformers, bi-encoders, cross-encoders), with practical experience setting up and managing vector databases (e.g. Qdrant, Weaviate, Milvus, pgvector) along with understanding trade-offs e.g. when to use sparse or dense embeddings (or both) etc;
 </li>
 <li>
 Classical NLP training and evaluating text classifiers, NER models, or other supervised/semi-supervised NLP models for domain-specific tasks.
 
 </li>
 </ul>
 
 In addition, the following would be an advantage:
 
 
 
 <ul>
 <li>
 Experience with knowledge graphs/triplestores/semantic web frameworks (e.g. Neo4j, RDF/SPARQL/OWL, Apache Jena).
 </li>
 <li>
 Practical experience with entity linking, concept normalisation, or ontology-driven NLP.
 </li>
 <li>
 Experience with retrieval-augmented generation (RAG) pipelines
 </li>
 <li>
 Familiarity with agentic AI frameworks and multi-agent orchestration (e.g. LangGraph, AutoGen).
 </li>
 <li>
 Good familiarity with the Azure ecosystem (Azure Kubernetes Service, Azure Container Registry, Azure DevOps, Azure Blob Storage, Azure Monitor, Azure Key Vault).
 
 
 </li>
 </ul>
 This is a hybrid role based in our office in London (Borough). You would be expected to be able to work from the office at least 1-2 days per week. Some travel is required for on-site client engagements as needed.
 
 
 
 
 Job Benefits
 
 
 
 <ul>
 <li>
 Competitive salary reviewed annually
 </li>
 <li>
 Work for a passionate, mission-driven company solving society&rsquo;s big problems
 </li>
 <li>
 Work flexible hours around life commitments with a focus on delivering company value rather than hours worked
 </li>
 <li>
 Ability to work remotely (excluding face-to-face Team Meetings and client meetings)
 </li>
 <li>
 Training and development opportunities
 </li>
 <li>
 25 days annual leave (plus bank holidays)
 </li>
 <li>
 Company pension
 </li>
 <li>
 Private medical insurance
 </li>
 <li>
 Generous enhanced parental leave policies
 </li>
 <li>
 Cycle to work scheme
 </li>
 <li>
 Flu Vaccinations,
 </li>
 <li>
 Eye Test and contribution towards Glasses for VDU use
 </li>
 </ul>
 
 Employee Assistance Programme
 
 <ul>
 <li>
 Mental health and wellbeing support
 </li>
 <li>
 Remote GP access
 </li>
 <li>
 Counselling/therapy
 </li>
 <li>
 Physiotherapy
 </li>
 <li>
 Medical second opinions
 
 
 </li>
 </ul>
</div>

AI NLP Engineer

explaino

<div>
 
 Join explaino, the operating system for enterprise knowledge transfer. Backed by Europe&rsquo;s greatest early-stage VC EWOR and leading clients like Schneider Electric, Coop, Sparkassen, and AOK, we transform complex documents into dynamic explainer videos &mdash; fully automated in less than 30 minutes. We&rsquo;re now looking for a Founding AI Engineer to take ownership of our AI core and shape the future of video generation with NLP, LLMs, and computer vision.
 
 
 Aufgaben
 
 
 This is not a regular IC role &mdash; it's a unique opportunity to become a founding team member. You&rsquo;ll work closely with the Founder to lead the AI stack behind explaino&rsquo;s transformation pipeline.
 
 
 <ol>
 
 <li>
 Own, expand, and optimize our end-to-end AI pipeline (from text input to video frame output)
 </li>
 
 <li>
 Apply state-of-the-art NLP and LLM techniques (incl. fine-tuning, retrieval augmentation, advanced prompting strategies)
 </li>
 
 <li>
 Build systems that combine language, computer vision, and structured video logic
 </li>
 
 <li>
 Minimize hallucinations, ensure structure, and validate output with classic NLP techniques
 </li>
 
 </ol>
 
 Qualifikation
 
 
 Experience as a professional AI Engineer, Data Analyst, Applied Research Scientist or similar
 
 
 <ol>
 
 <li>
 Data analytics skills to continuously evaluate and improving model output
 </li>
 
 <li>
 2 years+ experience in Python and Huggingface.
 </li>
 
 <li>
 Strong NLP knowledge from traditional techniques to transformers + basic understanding of Comp. Vision
 </li>
 
 <li>
 German language proficiency on C2 level
 </li>
 
 <li>
 Availability on-site in Garching near Munich.
 </li>
 
 <li>
 Experience with the following would be beneficial: PyTorch, Azure ML Studio, Optuna, Langchain, Peft &amp; Lora, Bitsandbytes, Scikit, NLTK, Numpy, Pandas, etc.
 </li>
 
 </ol>
 
 Benefits
 
 <ol>
 
 <li>
 Part of an innovative and dynamic team in a growing tech startup.
 </li>
 
 <li>
 Direct influence the company&rsquo;s success and product development.
 </li>
 
 <li>
 Direct collaboration with the Founder.
 </li>
 
 <li>
 Option to participate in the company's success through virtual shares (VSOPs).
 </li>
 
 <li>
 Building an innovative, leading AI-based video generation backend leveraging various state-of-the-art ML/NLP/CV technologies.
 </li>
 
 <li>
 A creative and inspiring work environment.
 </li>
 
 </ol>
 
 
 If you are as ambitious as we are and willing to go the extra mile, we are very much looking forward to your application!
 
</div>

Founding AI/NLP Engineer (m/w/d)

XA Group

<div></div><div><div><div><div>2-5 Years</div>
<div><div>Engineering</div>
<div>Remote</div>
</div></div></div><div><div>Engineering</div>
<div>Remote</div>
We are looking for an AI/ML Engineer with expertise in NLP, Generative AI, and Language Models (LLMs), particularly in Retrieval-Augmented Generation (RAG). The ideal candidate should be proficient in Python and experienced with FastAPI and Streamlit for building user-friendly applications and rapid prototyping. The role involves collaborating on AI model development, conducting evaluations to improve performance, and delivering Proofs of Concept (POCs). You will work closely with cross-functional teams to integrate and deploy AI solutions, while also staying updated on emerging frameworks. Strong communication skills and the ability to manage project delivery are key. Experience with agentic frameworks and basic machine learning concepts is a plus.
<div>Responsibilities:
<ul><li>Collaborate in developing and enhancing NLP, RAG, and LLM-related projects and ensuring their effectiveness and robustness.</li></ul>
<ul><li>Proactive in gathering and understanding data and requirements for the projects.</li></ul>
<ul><li>Conduct model evaluations using established metrics and provide insights for model improvement.</li></ul>
<ul><li>Rapidly build Proof of Concepts (POCs) by working closely with internal and external stakeholders.</li></ul>
<ul><li>Confident is using FastAPI and Streamlit to create effective, user-friendly interfaces and endpoints as needed.</li></ul>
<ul><li>Coordinate with Product managers, DevOps and other team members to manage integrations and ensure successful testing.</li></ul>
<ul><li>Actively research and adopt emerging frameworks and methodologies to enhance our applications.</li></ul>
<ul><li>Exhibit strong communication skills, ensuring clear updates and feedback loops with all stakeholders.</li></ul> 
Key Skills and Expertise Required:
<ul><li>Programming &amp; Frameworks: Proficient in Python, with experience in FastAPI and Streamlit for rapid prototyping.</li></ul>
<ul><li>NLP &amp; Generative AI: Strong foundation in NLP, Generative AI, Language Models (LLMs), and Retrieval-Augmented Generation (RAG).</li></ul>
<ul><li>Model Development &amp; Evaluation: Capable of building and evaluating AI and ML models and evaluate with metrics to assess model performance.</li></ul>
<ul><li>Agentic Frameworks: Familiarity with agentic frameworks (e.g., LangGraph or alternatives) is preferred. (good to have)</li></ul>
<ul><li>Basic Machine Learning and Deep Learning: Sound knowledge of foundational ML and DL concepts.</li></ul>
<ul><li>Project Delivery &amp; Coordination: Demonstrated ability to collaborate with DevOps and other stakeholders for smooth integration, testing, and deployment of AI applications.</li></ul>
<ul><li>Experience Range: 2-5 years in NLP and Generative AI</li></ul></div></div></div>

Data Scientist

TrioSoft Technologies

<ul><li><div>Experience: 1 - 3 Years</div></li><li><div>
Openings: 2</div></li><li><div>
Package: as per industry standards</div></li></ul>
 <div><div><div><h2 class="jobSectionHeader">Job Summary</h2>
We are looking for a Machine Learning Engineer with experience in NLP and Conversational AI to build intelligent AI Voice Agents and Chatbot solutions. The candidate will be responsible for designing, training, evaluating, and deploying intent classification models, entity recognition systems, and hybrid AI pipelines combining Machine Learning with Large Language Models (LLMs). 
<h2 class="jobSectionHeader">Key Responsibilities</h2>
<ul><li>Design and develop NLP models for Intent Classification and Entity Recognition.
</li><li>Prepare, clean, and label conversational datasets.
</li><li>Train, fine-tune, and evaluate machine learning models for conversational AI.
</li><li>Build hybrid AI systems using ML-based intent detection with LLM fallback.
</li><li>Develop conversation routing logic based on confidence scores.
</li><li>Optimize model accuracy, latency, and inference performance.
</li><li>Integrate ML models with Python backend services and REST APIs.
</li><li>Design conversation flows for AI Voice Bots and Chatbots.
</li><li>Work with Prompt Engineering for LLM fallback responses.
</li><li>Build and maintain RAG (Retrieval-Augmented Generation) pipelines.
</li><li>Monitor model performance and retrain models when required.
</li><li>Collaborate with Backend, Frontend, and Product teams.
</li></ul></div></div><div><div><h2 class="jobSectionHeader">Required Skills</h2>
<ul><li>Strong Python programming
</li><li>Machine Learning
</li><li>Natural Language Processing (NLP)
</li><li>Intent Classification
</li><li>Text Classification
</li><li>Named Entity Recognition (NER)
</li><li>scikit-learn
</li><li>PyTorch or TensorFlow
</li><li>Hugging Face Transformers
</li><li>Sentence Transformers
</li><li>Model Training &amp; Fine-Tuning
</li><li>Model Evaluation (Precision, Recall, F1-Score)
</li><li>REST APIs
</li><li>Git
</li><li>Prompt Engineering
</li><li>RAG
</li><li>Vector Databases (Qdrant, Pinecone, Weaviate, Chroma)
</li><li>LangChain / LangGraph / LlamaIndex
</li></ul><h2 class="jobSectionHeader">Good to Have</h2>
<ul><li>Experience building AI Voice Bots
</li><li>Hybrid ML + LLM architectures
</li><li>Conversation Flow Design
</li><li>Speech-to-Text (STT) and Text-to-Speech (TTS) integrations
</li><li>Production deployment of ML models</li></ul></div></div></div>

Machine Learning Engineer (NLP / Conversational AI)

Advansys

<div>
 Key Responsibilities
 
 
 <ul>
 <li>
 Lead the entire ML lifecycle from data collection and analysis to model deployment, monitoring, and optimization
 </li>
 <li>
 Apply deep learning and NLP techniques to develop solutions, potentially enhancing systems like search or recommendation engines
 </li>
 <li>
 Design and implement end-to-end ML pipelines, incorporating MLOps best practices for CI/CD, containerization (Docker, Kubernetes), and cloud deployment (AWS, GCP, Azure)
 </li>
 <li>
 Utilize LLM knowledge, including prompt engineering and fine-tuning, to build advanced generative AI applications and conversational AI solutions
 </li>
 <li>
 Perform comprehensive data analytics, including statistical analysis and feature engineering, to inform model development and extract actionable insights from large datasets
 </li>
 <li>
 Write production-quality, robust code in Python (and potentially other languages like Java or Scala), ensuring code quality through reviews and testing
 </li>
 <li>
 Collaborate with cross-functional teams, including data scientists, data engineers, and product managers, to translate business requirements into technical ML solutions
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 Required Skills and Qualifications
 
 
 <ul>
 <li>
 Proven experience as a Machine Learning Engineer with a strong portfolio of deployed production models
 </li>
 <li>
 Proficiency in Python and relevant ML frameworks/libraries (e.g., TensorFlow, PyTorch, scikit-learn)
 </li>
 <li>
 Expertise in data science methodologies, statistical analysis, and data analytics
 </li>
 <li>
 Hands-on experience with MLOps tools and practices for managing the ML application lifecycle
 </li>
 <li>
 Strong understanding of NLP and experience with LLMs and prompt engineering techniques
 </li>
 <li>
 Solid software engineering background with knowledge of data structures, algorithms, and system design
 </li>
 <li>
 Excellent problem-solving, communication, and collaboration skills
 </li>
 </ul>
</div>

Senior Machine Learning Engineer

<div>Key Responsibilities<ul><li>
Lead the entire ML lifecycle from data collection and analysis to model deployment, monitoring, and optimization.</li><li>
Apply deep learning and NLP techniques to develop solutions, potentially enhancing systems like search or recommendation engines.</li><li>
Design and implement end-to-end ML pipelines, incorporating MLOps best practices for CI/CD, containerization (Docker, Kubernetes), and cloud deployment (AWS, GCP, Azure).</li><li>
Utilize LLM knowledge, including prompt engineering and fine-tuning, to build advanced generative AI applications and conversational AI solutions.</li><li>
Perform comprehensive data analytics, including statistical analysis and feature engineering, to inform model development and extract actionable insights from large datasets.</li><li>
Write production-quality, robust code in Python (and potentially other languages like Java or Scala), ensuring code quality through reviews and testing.</li><li>
Collaborate with cross-functional teams, including data scientists, data engineers, and product managers, to translate business requirements into technical ML solutions.</li></ul> 

Requirements 
Required Skills and Qualifications<ul><li>
Proven experience as a Machine Learning Engineer with a strong portfolio of deployed production models.</li><li>
Proficiency in Python and relevant ML frameworks/libraries (e.g., TensorFlow, PyTorch, scikit-learn).</li><li>
Expertise in data science methodologies, statistical analysis, and data analytics.</li><li>
Hands-on experience with MLOps tools and practices for managing the ML application lifecycle.</li><li>
Strong understanding of NLP and experience with LLMs and prompt engineering techniques.</li><li>
Solid software engineering background with knowledge of data structures, algorithms, and system design.</li><li>
Excellent problem-solving, communication, and collaboration skills.</li></ul></div>

Aliqan Technologies

Job Description &ndash; GenAI EngineerPosition: GenAI Engineer Experience: 5.5 &ndash; 9 Years Location: Mumbai, Bangalore, Gurugram, Chennai Work Mode: Hybrid (3 Days Work From Office &ndash; Mandatory) Work Location: Candidate must be willing to work from the client location. CTC: Up to ₹36 LPAAbout the RoleWe are looking for an experienced GenAI Engineer with strong expertise in Large Language Models (LLMs), Generative AI, NLP, Computer Vision, and cloud technologies. The ideal candidate should be capable of designing and developing end-to-end AI-powered solutions while working closely with cross-functional teams to build scalable, production-ready applications.Key Responsibilities<ul><li>Design, develop, and deploy advanced solutions using Large Language Models (LLMs).</li><li>Take complete ownership of end-to-end solution development from design to deployment.</li><li>Research and stay updated with the latest advancements in Generative AI, LLMs, and AI frameworks.</li><li>Develop reusable code libraries, frameworks, and tools for AI application development.</li><li>Participate in code reviews and ensure adherence to coding standards and best practices.</li><li>Contribute across the complete Software Development Life Cycle (SDLC), including design, development, testing, deployment, and maintenance.</li><li>Collaborate with product managers, engineering teams, and stakeholders to integrate AI solutions into enterprise applications.</li><li>Analyze business problems and translate them into scalable AI-driven solutions.</li><li>Troubleshoot, optimize, and improve AI models and application performance.</li><li>Communicate effectively with technical and non-technical stakeholders.</li></ul>Required Skills1. Natural Language Processing (NLP)Hands-on experience in one or more of the following:<ul><li>Use case classification</li><li>Topic modeling</li><li>Question Answering (Q&amp;A)</li><li>Chatbots</li><li>Enterprise Search</li><li>Document AI</li><li>Text Summarization</li><li>Content Generation</li></ul>OR2. Computer Vision &amp; Audio AIHands-on experience in:<ul><li>Image classification</li><li>Object detection</li><li>Image segmentation</li><li>Image generation</li><li>Audio analysis</li><li>Video analysis</li></ul>Generative AI &amp; LLMsSaaS LLM PlatformsExperience with:<ul><li>LangChain</li><li>LlamaIndex</li><li>Vector Databases</li><li>Prompt Engineering (Chain of Thought, Tree of Thought, ReAct, AI Agents)</li><li>Azure OpenAI</li><li>Google Vertex AI</li><li>AWS Bedrock</li><li>Multi-modal AI (Text, Audio, Image, Video)</li></ul>Open Source LLMsKnowledge of:<ul><li>Hugging Face</li><li>TensorFlow</li><li>PyTorch</li><li>LLM Fine-tuning (PEFT)</li><li>RLHF (Reinforcement Learning from Human Feedback)</li><li>Quantization</li><li>Data Annotation Workflows</li><li>GPU Utilization and Optimization</li></ul>Cloud TechnologiesHands-on experience with one or more cloud platforms:<ul><li>Microsoft Azure</li><li>Amazon Web Services (AWS)</li><li>Google Cloud Platform (GCP)</li></ul>Preferred:<ul><li>Cloud Certification (Azure/AWS/GCP)</li></ul>Application Development SkillsStrong experience in:<ul><li>Python</li><li>Docker</li><li>FastAPI / Django / Flask</li><li>Git &amp; Version Control</li><li>REST APIs</li><li>Microservices Architecture</li></ul>Required Qualifications<ul><li>5.5&ndash;9 years of overall software development experience.</li><li>Strong experience in Generative AI and LLM-based application development.</li><li>Excellent analytical and problem-solving skills.</li><li>Strong communication and collaboration skills.</li><li>Ability to work independently and take ownership of projects.</li><li>Experience building scalable, production-ready AI applications.</li></ul>Preferred Skills<ul><li>Experience with RAG (Retrieval-Augmented Generation) architectures.</li><li>Knowledge of Vector Databases (Pinecone, FAISS, ChromaDB, Weaviate, Milvus, etc.).</li><li>Experience deploying AI applications on cloud platforms.</li><li>Exposure to MLOps and CI/CD pipelines.</li><li>Experience with AI Agents and Agentic AI frameworks.</li></ul>Pay: ₹2,500,000.00 - ₹3,600,000.00 per yearWork Location: Hybrid remote in Bangalore City, Bengaluru, Karnataka

Generative AI Engineer

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AI NLP Engineer

Founding AI/NLP Engineer (m/w/d)

Data Scientist

Machine Learning Engineer (NLP / Conversational AI)

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Generative AI Engineer